Introduction

Hui Lin

Lead Data Scientist @Netlify

2019-04-15

Schedule

Topic Time
Introduction to Data Science 8:15 - 8:45
Deep Learning 1 8:45 - 10:15
Deep Learning 1 Hands-on 10:15 - 10:30
Break 10:30 - 10:45
Deep Learning 2 10:45 - 11:30
Deep Learning 3 11:30 - 12:00
Deep Learning Hands-on Session 12:00 - 12:15

Course Website

https://idad2019.netlify.com/

The term no one really defined

Data science is the discipline of making data useful. Ok…so what is it?

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What is “hard-core pornography”?

Jacobellis v. Ohio, 378 U.S. 184 (1964), was a United States Supreme Court decision handed down in 1964 involving whether the state of Ohio could, consistent with the First Amendment, ban the showing of the Louis Malle film The Lovers (Les Amants), which the state had deemed obscene.

What is “hard-core pornography”?

“I know it when I see it.” (Justice Potter Stewart)

Three tracks of data science

(It is a group work from https://github.com/brohrer/academic_advisory/blob/master/authors.md !)

Engineering

  1. Data environment: data storage, Kafka platform, Hadoop and Spark cluster etc.

  2. Data management: parsing the logs, web scraping, API queries, and interrogating data streams.

  3. Production: integrate model and analysis into the production system

Engineering - Production

Data Pipeline

Analysis

  1. Domain knowledge

  2. Exploratory analysis

  3. Story telling

Modeling

  1. Supervised learning

  2. Unsupervised learning

  3. Customized model development

General Process of Modeling/Analytics

Three tracks of data science

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Three tracks of data science

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Three tracks of data science

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Data Science Curriculum Roadmap

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What can (should) data science do?

Data Science Hierarchy of Needs

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Data Science Types v.s Needs

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Data Science Types v.s Needs

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Data Science Types v.s Needs

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Data Science Types v.s Needs

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Types of Questions (Modeling/Analytics)

Types of Questions (Modeling/Analytics)

Where does data science belong in your organization?

A standalone team

Where does data science belong in your organization?

An embedded model

Where does data science belong in your organization?

Integrated team